Detection of Carried and Dropped Objects in Surveillance Video

摘要

DARPA's Mind's Eye Program aims to develop a smart camera surveillance system that can autonomously monitor a scene and report back human-readable text descriptions of activities that occur in the video. An important aspect is whether objects are brought into the scene, exchanged between persons, left behind, picked up, etc. While some objects can be detected with an object-specific recognizer, many others are not well suited for this type of approach. For example, a carried object may be too small relative to the resolution of the camera to be easily identifiable, or an unusual object, such as an improvised explosive device, may be too rare or unique in its appearance to have a dedicated recognizer. Hence, a generic object detection capability, which can locate objects without a specific model of what to look for, is used. This approach can detect objects even when partially occluded or overlapping with humans in the scene.